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Automatic mouse ultrasound detector (A-MUD): A new tool for processing rodent vocalizations
House mice (Mus musculus) emit complex ultrasonic vocalizations (USVs) during social and sexual interactions, which have features similar to bird song (i.e., they are composed of several different types of syllables, uttered in succession over time to form a pattern of sequences). Manually processin...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5519055/ https://www.ncbi.nlm.nih.gov/pubmed/28727808 http://dx.doi.org/10.1371/journal.pone.0181200 |
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author | Zala, Sarah M. Reitschmidt, Doris Noll, Anton Balazs, Peter Penn, Dustin J. |
author_facet | Zala, Sarah M. Reitschmidt, Doris Noll, Anton Balazs, Peter Penn, Dustin J. |
author_sort | Zala, Sarah M. |
collection | PubMed |
description | House mice (Mus musculus) emit complex ultrasonic vocalizations (USVs) during social and sexual interactions, which have features similar to bird song (i.e., they are composed of several different types of syllables, uttered in succession over time to form a pattern of sequences). Manually processing complex vocalization data is time-consuming and potentially subjective, and therefore, we developed an algorithm that automatically detects mouse ultrasonic vocalizations (Automatic Mouse Ultrasound Detector or A-MUD). A-MUD is a script that runs on STx acoustic software (S_TOOLS-STx version 4.2.2), which is free for scientific use. This algorithm improved the efficiency of processing USV files, as it was 4–12 times faster than manual segmentation, depending upon the size of the file. We evaluated A-MUD error rates using manually segmented sound files as a ‘gold standard’ reference, and compared them to a commercially available program. A-MUD had lower error rates than the commercial software, as it detected significantly more correct positives, and fewer false positives and false negatives. The errors generated by A-MUD were mainly false negatives, rather than false positives. This study is the first to systematically compare error rates for automatic ultrasonic vocalization detection methods, and A-MUD and subsequent versions will be made available for the scientific community. |
format | Online Article Text |
id | pubmed-5519055 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-55190552017-08-07 Automatic mouse ultrasound detector (A-MUD): A new tool for processing rodent vocalizations Zala, Sarah M. Reitschmidt, Doris Noll, Anton Balazs, Peter Penn, Dustin J. PLoS One Research Article House mice (Mus musculus) emit complex ultrasonic vocalizations (USVs) during social and sexual interactions, which have features similar to bird song (i.e., they are composed of several different types of syllables, uttered in succession over time to form a pattern of sequences). Manually processing complex vocalization data is time-consuming and potentially subjective, and therefore, we developed an algorithm that automatically detects mouse ultrasonic vocalizations (Automatic Mouse Ultrasound Detector or A-MUD). A-MUD is a script that runs on STx acoustic software (S_TOOLS-STx version 4.2.2), which is free for scientific use. This algorithm improved the efficiency of processing USV files, as it was 4–12 times faster than manual segmentation, depending upon the size of the file. We evaluated A-MUD error rates using manually segmented sound files as a ‘gold standard’ reference, and compared them to a commercially available program. A-MUD had lower error rates than the commercial software, as it detected significantly more correct positives, and fewer false positives and false negatives. The errors generated by A-MUD were mainly false negatives, rather than false positives. This study is the first to systematically compare error rates for automatic ultrasonic vocalization detection methods, and A-MUD and subsequent versions will be made available for the scientific community. Public Library of Science 2017-07-20 /pmc/articles/PMC5519055/ /pubmed/28727808 http://dx.doi.org/10.1371/journal.pone.0181200 Text en © 2017 Zala et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Zala, Sarah M. Reitschmidt, Doris Noll, Anton Balazs, Peter Penn, Dustin J. Automatic mouse ultrasound detector (A-MUD): A new tool for processing rodent vocalizations |
title | Automatic mouse ultrasound detector (A-MUD): A new tool for processing rodent vocalizations |
title_full | Automatic mouse ultrasound detector (A-MUD): A new tool for processing rodent vocalizations |
title_fullStr | Automatic mouse ultrasound detector (A-MUD): A new tool for processing rodent vocalizations |
title_full_unstemmed | Automatic mouse ultrasound detector (A-MUD): A new tool for processing rodent vocalizations |
title_short | Automatic mouse ultrasound detector (A-MUD): A new tool for processing rodent vocalizations |
title_sort | automatic mouse ultrasound detector (a-mud): a new tool for processing rodent vocalizations |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5519055/ https://www.ncbi.nlm.nih.gov/pubmed/28727808 http://dx.doi.org/10.1371/journal.pone.0181200 |
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